Quantitative#123

Scenario/Stress Allocation Engine

This is a stress-testing allocator, not a trade signal. Define a handful of discrete macro scenarios (Fed cut, election flip, war escalation) and require the whole book's profit-and-loss under every one of them to stay inside a loss tolerance, only adding new capital where it improves the worst scenario. The benefit is a portfolio that survives across joint outcomes rather than one tuned to the single most-likely case.

What you need to run it

Scenario set with per-market payoff mapping
Joint scenario P&L matrix across the book
Constrained optimizer minimizing worst-case loss
Capital-allocation interface to size new entries

Where this applies

Markets on Polymarket where scenario/stress allocation engine is the natural play:

Will the Fed cut rates at the next FOMC meeting? (Fed-cut scenario driver)
Will Republicans hold the 2026 House majority? (election-flip scenario driver)
Will Israel and Iran reach a ceasefire by December 31, 2026? (war-escalation scenario driver)

Capabilities this demands

Model / quantRisk managementManual researchData ingestion

At a glance

CategoryQuantitative

Requirements4

CapabilitiesModel / quant, Risk management, Manual research, Data ingestion

VenuePolymarket (CLOB, Polygon)

Build it

Related quantitative strategies

This is documentation, not advice. Poly Research & Robotics publishes how these strategies work because the method should be checkable — not as a recommendation to trade them. See the full strategy database (147 strategies) or the data resources directory.